基于遗传算法的带式输送机多变量优化节能运输策略研究

摘要

针对带式输送机节能运输策略研究,分别建立输送机运行过程的能量消耗与用电成本数学模型,得出影响输送机运行能耗与用电成本的关键因素,通过分时电价等约束条件,采用遗传算法对模型变量进行全局优化,寻找各时段带式输送机运输煤量与运行速度的节能最优解,并对比优化节能策略所带来的经济效益.对比结果表明:在现有技术与设备不需要变动的前提下,通过优化带式输送机的运输策略,可分别节省约45%的能量消耗与42%的用电成本,有效的降低了煤炭运输成本,提高煤矿企业经济效益,从而实现煤炭开采与运输环节的精细化管理.%Aiming at the energy saving transportation strategy for belt conveyors,the mathematic model of energy consumption for belt conveyor and the model for electric cost in its operating condition were established,and the key influence factors for energy consumption and electric cost was obtained.The genetic global optimization algorithm was adopted to find the optimal coal flow and the operating speed by time-of-use power price and other constraints.Moreover,an economy benefit comparison of optimal energy saving transportation strategy and its normal operation strategy was taken to show the benefits.The results of comparison shows that under the current circumstance of technology and equipment,a 45% energy and 42% electric cost can be saved with the optimal energy saving transportation strategy,which brings down the coal transportation cost and enhances the economy benefit of coal mines,thus the delicacy management of mining and transportation of the coal mine can be achieved.